Method for Simulating Dose Reduction in Digital Breast Tomosynthesis

Abstract

The goal of this project is to develop a practical and accurate method for simulating dose reduction in digital breast tomosynthesis images (DBT). DBT is a new imaging modality that provides a 3D reconstruction of the breast anatomy. The 3D visualization of the breast anatomy through DBT minimizes issues related to tissue overlap and thus allows better rates of detection and characterization of lesions. Recent studies have shown that DBT yields higher sensitivity and specificity compared to conventional 2D mammography, and may substitute 2D mammography in breast cancer screening. However, during the exam the patient is exposed to small doses of radiation. Thus, it is important to reach an optimized relation between image quality and radiation dose, respecting the ALARA (As Low As Reasonably Achievable) principle. To conduct studies about the optimal operation point, it is common to perform the injection of quantum noise in clinical images to simulate the quality of lower-dose images. However, standard methods described in the literature are not appropriate for DBT images, due to differences in the acquisition process and geometry. Thus, the studies that explore the operation point of DBT systems, in terms of radiation dose, are limited. This project proposes the development of a simulation method specifically designed for DBT images. It will incorporate properties such as the electronic noise, spatial and frequency dependency of the noise. This will be achieved by using a novel concept of noise insertion on a variance-stabilizing domain, as proposed in previous work published by our group. Additionally, the proposed method will be validated using human observer experiments and clinical images from patients. By the end of this project, our goal is to conduct a final study about the limits of dose savings in DBT through the reduction of radiation dose. (AU)